A Novel NLOS Suppression Algorithm for Indoor Location based on FCM and REKF

Abstarct. The indoor positioning based on wireless sensor networks (WSN) has become one of the research hotpots. However, the NLOS propagation of the distance signals greatly challenges the accuracy and robustness of the algorithm. In this paper, we take the suppression of NLOS as the core goal and...

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Bibliographic Details
Published in:Journal of physics. Conference series 2022-03, Vol.2216 (1), p.12067
Main Authors: Jin, JiaWei, Cheng, Long, Zhou, JiaBao
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Extended Kalman filter
Physics
Wireless sensor networks
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Summary:Abstarct. The indoor positioning based on wireless sensor networks (WSN) has become one of the research hotpots. However, the NLOS propagation of the distance signals greatly challenges the accuracy and robustness of the algorithm. In this paper, we take the suppression of NLOS as the core goal and proposed the FCM-REKF-based positioning method. We firstly identify the signal states through the fuzzy c-means clustering (FCM), for the measurement distance judged to be NLOS, a refactoring method based on FCM is used. Then the corrected distance is smoothed by Kalman filter, and the Robust Extended Kalman Filter is used to calculate the final position. The simulation results show that our method has higher accuracy than EKF, REKF and IMM-EKF under NLOS environment.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2216/1/012067